1. Field of Invention
The field of the currently claimed embodiments of this invention relates to methods and systems for locating objects embedded within a body, and more particularly to methods and systems for locating objects embedded within a body based on reduced computational requirements.
2. Discussion of Related Art
C-arm fluoroscopy is widely used for visual assessment during clinical procedures. However, it is limited in that it cannot show soft tissues or organs of interest and other relevant structures. On the other hand, use of other imaging modalities such as ultrasound during clinical procedures provides real-time visualization of the tissue/organ of interest but does not provide radiographic information. Fusion of these complementary imaging modalities would provide benefits during many procedures.
For example, interventional tool registration with soft tissue would benefit from being able to accurately view the tool and the soft tissue of interest simultaneously during a medical procedure. The procedure could be performed with greater precision through improved tool visualization and registration with the soft tissues undergoing the procedure. Further, the ability to visualize the soft tissue using another imaging modality such as ultrasound provides real time information to the clinician performing the procedure.
Carcinoma of the prostate is one of the most prevalent and fatal cancers in men in North America. Prostate cancer alone accounts for 25% of cancer cases and 9% of cancer deaths in men with approximately 200,000 estimated new cases and 30,000 estimated deaths each year in the United States alone. During the past decade, ultrasound-guided low dose rate (LDR) transperineal brachytherapy has become one of the popular choices of therapy for patients with early prostate cancer. It involves the implantation of radioactive seeds (either 125I or 103Pd) into the prostate in the patient. Brachytherapy involves the placement of radioactive pellets or “seeds” into or adjacent cancerous tissue of a patient. Brachytherapy makes it possible to treat the cancer with a high total dose of radiation in a concentrated area in a short period of time, and at the same time spare healthy tissues the treatment with radiation. The key to successful brachytherapy is the accurate placement of the seeds. However, faulty needle and seed placement often cause an insufficient dose to the cancer and/or inadvertent radiation of healthy tissues. The ability to perform dosimetry optimization during the procedure could change the standard of care in brachytherapy, but such function is not available today and it is unfortunate that implants are currently performed without an explicit dosimetry evaluation in the operating room. Generally, dosimetric analysis requires precise localization of the implanted seeds in relation to the cancerous tissue and surrounding anatomy. Brachytherapy success critically depends on adequately dosing the target gland by implanting a sufficient number and distribution of radioactive seeds while avoiding excessive radiation toxicity to adjacent organs, most notably urethra, bladder, and rectum.
In the contemporary prostate brachytherapy procedure, an implant plan is made either preoperatively or intraoperatively based on transrectal ultrasound (TRUS) imaging. The physician first contours the prostate and the planning target volume from ultrasound images acquired from TRUS probe, and then a treatment planning system is used to create a seed implant plan to deliver the prescribed dose to the target. During the implant procedure, the patient lies on his back with his legs in a high lithotomy position. The physician places the seeds into the planned locations in the prostate via needles inserted transperineally through a template guide using TRUS guidance as depicted in FIG. 1.
One of the greatest challenges of the current TRUS-guided implant method is that it is difficult to visualize the implanted seeds on TRUS. Seed positions may be estimated intraoperatively at the time of deposition based on visualization of the needle tip on TRUS images, but this method is subject to inaccuracies due to procedural variations such as patient motion, needle deviation, seed migration, and prostatic edema. As a consequence, seed positioning variations cannot be identified intraoperatively during the procedure. An additional seed implant session (which can be technically challenging) or supplemental external beam radiation is sometimes necessary to cover underdosed regions. The future direction of prostate brachytherapy involves the development of a system that intraoperatively assists the brachytherapist to achieve optimal dosimetric quality with a favorable dose profile to the target and surrounding normal tissues.
In order to achieve concurrent visualization of the anatomy and implanted seeds, systems that use ultrasound imaging and x-ray fluoroscopy have been proposed to permit both monitoring of the implant process and reconstruction of the implanted seeds for intraoperative treatment optimization. In particular, x-ray projection images can be acquired using conventional mobile c-arms and the three-dimensional (3-D) seed positions can be reconstructed from these data. The reconstructed seeds can then be registered to the prostate volume that is visualized using the TRUS images. Overall, this process provides sufficient information for the computation of an intraoperative dose distribution at intermediate implant stages in relation to the target from which a modification to the original seed placement plan can be computed and carried out during the same therapeutic procedure.
There has been extensive previous work on the reconstruction of brachytherapy seeds from multiple x-ray images. The most common approaches consist of the following tasks: (1) acquire several x-ray images from different orientations; (2) segment the seeds and find their two-dimensional (2-D) coordinates in every image; (3) determine which segmented seeds in each image correspond to the same physical seed (“seed matching”); and (4) compute the positions of each physical seed from the corresponding seeds (“triangulation”). In order to minimize the chances of having multiple, equally-valid solutions to this problem, at least three images are required. Regardless of the number of acquired images, the resulting optimization problem required for seed matching is computationally very expensive due to combinatorial explosion, which implies that most reconstruction algorithms must be approximate since carrying out an exhaustive search is too time-consuming for routine clinical practice. Most of the current approaches assume that every seed can be individually identified in every image; but, in reality, each image will generally contain some seeds whose projections overlap. Both the computational demands and the so-called “hidden seed problem” represent significant impediments to the routine application of currently known seed reconstruction methods in clinical practice.
In recent years, several methods have been proposed for solving the hidden seed problem. The use of a statistical classifier was explored to determine the number of seeds in a self-connected region in the segmented seed images, but it was prone to generate false positives or negatives that can critically influence the following reconstruction. There was an epipolar geometry-constrained pseudo-seed-matching strategy, but it requires a co-planar imaging constraint in order to use three images since epipolar geometry is defined only over two projections. There are tomosynthesis-based implant reconstruction methods, but these methods generally require a much larger number of images and wider image acquisition angles than seed-matching approaches for stable implant reconstruction, and are slow because the whole volume has to be reconstructed. The use of adaptive grouping techniques were also used in order to divide the seed images into groups for efficient seed reconstruction, but these methods have overdividing problems due to incorrect division of triplets (when three images are used), resulting in false positive seeds in the reconstruction.
In summary, existing seed reconstruction methods have at least one of the following fundamental limitations: (1) they are sensitive to pose errors of the imaging device, (2) they cannot resolve the hidden seed problem, (3) they require a large number of images, large image acquisition angles, and a long time to compute a converging solution, and (4) they require constrained motion of the imaging device, e.g., isocentric circular trajectory.
There thus remains the need for improved methods and systems for locating objects embedded within a body.